class_docstr: An Item-Item Recommender on BM25 distance between items
code: def __init__(self, K=20, K1=1.2, B=0.75, num_threads=0):
      super().__init__(K, num_threads)
      self.K1 = K1
      self.B = B
  
imports: import numpy
  from numpy import bincount, log, log1p, sqrt
  from scipy.sparse import coo_matrix, csr_matrix
  from ._nearest_neighbours import NearestNeighboursScorer, all_pairs_knn
  from .recommender_base import RecommenderBase
  from .utils import _batch_call
label_desc: Use image node_id 1 to create a new BM25Recommender object from inherited base classes: ItemItemRecommender with example: obj = BM25Recommender(K, K1, B, num_threads)